CRISPR-Cas9 off-targeting assessment with nucleic acid duplex energy parameters

<p>CRISPR-Cas9 off-targeting assessment with nucleic acid duplex energy parameters</p> <p>Collected and generated data for the paper</p> <p>## Data Tables</p> <p>Off-target score data for the ROC analysis using Haeussler dataset [2].</p> <p>Data from the table below is used to generate the Figure-2, Table-1 and Supplementary Figure-1 in the corresponding paper [1]. Don&#39;t forget to cite the corresponding studies as well if you use this table.</p> <ul> <li><strong>Haeussler_mm6_scores.csv.gz</strong>: This table includes the off-targeting scores of 1167036 off-target sequences, computed with CRISPRoff[1], CCTop[3], CFD[4], Cropit[5], Elevation (Elevation-score)[6], MIT[2,7] and VfoldCAS[8] methods. Off-target data has been taken from the Haeussler dataset [2].</li> </ul> <p>Analysis with CIRCLE-seq dataset [9]</p> <p>Data in all the three tables below has been generated to analyze the CIRCLE-seq dataset [9]. This data is further used to generate the Figure-3, Figure-4, and Supplementary Figure-4 in the corresponding paper. Don&#39;t forget to cite the corresponding studies as well if you use these tables.</p> <ul> <li> <p><strong>CIRCLEseq_known_off_scores.csv.gz</strong>: This table is used when generating the Figure-3 in the paper. It includes the 7 different off-targeting scores of CIRCLE-seq reported off-target sequences and the read counts from CIRCLE-seq experiments.</p> </li> <li> <p><strong>CIRCLEseq_mm6_off_scores.csv.gz</strong>: This table is used when generating the Figure-4 in the paper. It includes the 7 different off-targeting scores of RIsearch2(v2.1)[10] based off-target predictions for CIRCLE-seq gRNAs.</p> </li> <li> <p><strong>CIRCLEseq_specificities.csv.gz</strong>: This table is used when generating the Supplementary Figure-4 in the supplementary document of the paper. It includes the specificty scores of CIRCLE-seq gRNAs, computed with CRISPRspec[1], MIT[2,7], MIT*[1,2,7] and Elevation (Elevation-aggregate)[6] methods.</p> </li> </ul> <p>Analysis with SITE-seq dataset [11]</p> <p>Data in all the three tables below has been generated to analyze the SITE-seq dataset [11]. This data is further used to generate the Figure-5, Supplementary Figure-2 and Supplementary Figure-3 in the corresponding paper. Don&#39;t forget to cite the corresponding studies as well if you use these tables.</p> <ul> <li> <p><strong>SITEseq_known_off_scores.csv.gz</strong>: This table is used when generating the Supplementary Figure-2 in the supplementary document of the paper. It includes the 7 different off-targeting scores of SITE-seq reported off-target sequences and the read counts from SITE-seq experiments.</p> </li> <li> <p><strong>SITEseq_mm6_off_scores.csv.gz</strong>: This table is used when generating the Supplementary Figure-3 in the supplementary document of the paper. It includes the 7 different off-targeting scores of RIsearch2(v2.1) based off-target predictions for SITE-seq gRNAs.</p> </li> <li> <p><strong>SITEseq_specificities.csv.gz</strong>: This table is used when generating the Figure-5 in the paper. It includes the 4 different specificty scores of SITE-seq gRNAs.</p> </li> </ul> <p>Specificity-Efficiency Analysis</p> <p>This data is used to generate the Figure-6 and Supplementary Figure-5 in the corresponding paper. Don&#39;t forget to cite the corresponding studies as well if you use these tables.</p> <ul> <li><strong>Doench_Wang_specificity_grps.csv.gz</strong>: This table includes the specificity group of 3802 gRNA/on-target sequences, computed with CRISPRspec and MIT methods. gRNA sequence and modulation frequency data have been taken from the Haeussler dataset [2].</li> </ul> <p>## Citation</p> <p>If you find this data useful for your research, please cite the following works where appropriate:</p> <ol> <li>[Our citation comes here]</li> <li>Haeussler, M., Schonig, K., Eckert, H., Eschstruth, A., Mianne, J., Renaud, J.B., Schneider-Maunoury, S., Shkumatava, A., Teboul, L., Kent, J., Joly, J.S., Concordet, J.P.: Evaluation of off-target and on-target scoring algorithms and integration into the guide RNA selection tool CRISPOR. Genome Biol. 17(1), 148 (2016). <a href="https://www.ncbi.nlm.nih.gov/pubmed/27380939">PMID 27380939</a></li> <li>Stemmer, M., Thumberger, T., Del Sol Keyer, M., Wittbrodt, J., Mateo, J.L.: CCTop: An Intuitive, Flexible and Reliable CRISPR/Cas9 Target Prediction Tool. PLoS ONE 10(4), 0124633 (2015). <a href="https://www.ncbi.nlm.nih.gov/pubmed/25909470">PMID 25909470</a></li> <li>Doench, J.G., Fusi, N., Sullender, M., Hegde, M., Vaimberg, E.W., Donovan, K.F., Smith, I., Tothova, Z., Wilen, C., Orchard, R., Virgin, H.W., Listgarten, J., Root, D.E.: Optimized sgRNA design to maximize activity and minimize off-target effects of CRISPR-Cas9. Nat. Biotechnol. 34(2), 184&ndash;191 (2016). <a href="https://www.ncbi.nlm.nih.gov/pubmed/26780180">PMID 26780180</a></li> <li>Singh, R., Kuscu, C., Quinlan, A., Qi, Y., Adli, M.: Cas9-chromatin binding information enables more accurate CRISPR off-target prediction. Nucleic Acids Res. 43(18), 118 (2015). <a href="https://www.ncbi.nlm.nih.gov/pubmed/26032770">PMID 26032770</a></li> <li>Listgarten, J., Weinstein, M., Kleinstiver, B.P., Sousa, A.A., Joung, J.K., Crawford, J., Gao, K., Hoang, L., Elibol, M., Doench, J.G., Fusi, N.: Prediction of off-target activities for the end-to-end design of CRISPR guide RNAs. Nature Biomedical Engineering 2, 38&ndash;47 (2018). <a href="https://www.ncbi.nlm.nih.gov/pubmed/29998038">PMID 29998038</a></li> <li>Hsu, P.D., Scott, D.A., Weinstein, J.A., Ran, F.A., Konermann, S., Agarwala, V., Li, Y., Fine, E.J., Wu, X., Shalem, O., Cradick, T.J., Marraffini, L.A., Bao, G., Zhang, F.: DNA targeting specificity of RNA-guided Cas9 nucleases. Nat. Biotechnol. 31(9), 827&ndash;832 (2013). <a href="https://www.ncbi.nlm.nih.gov/pubmed/23873081">PMID 23873081</a></li> <li>Xu, X., Duan, D., Chen, S.J.: CRISPR-Cas9 cleavage efficiency correlates strongly with target-sgRNA folding stability: from physical mechanism to off-target assessment. Sci Rep 7(1), 143 (2017). <a href="https://www.ncbi.nlm.nih.gov/pubmed/28273945">PMID 28273945</a></li> <li>Tsai, S.Q., Nguyen, N.T., Malagon-Lopez, J., Topkar, V.V., Aryee, M.J., Joung, J.K.: CIRCLE-seq: a highly sensitive in vitro screen for genome-wide CRISPR-Cas9 nuclease off-targets. Nat. Methods 14(6), 607&ndash;614 (2017). <a href="https://www.ncbi.nlm.nih.gov/pubmed/28459458">PMID 28459458</a></li> <li>Alkan, F., Wenzel, A., Palasca, O., Kerpedjiev, P., Rudebeck, A.F., Stadler, P.F., Hofacker, I.L., Gorodkin, J.: RIsearch2: suffix array-based large-scale prediction of RNA-RNA interactions and siRNA off-targets. Nucleic Acids Res. (2017). <a href="https://www.ncbi.nlm.nih.gov/pubmed/28108657">PMID 28108657</a></li> <li>Cameron, P., Fuller, C.K., Donohoue, P.D., Jones, B.N., Thompson, M.S., Carter, M.M., Gradia, S., Vidal, B., Garner, E., Slorach, E.M., Lau, E., Banh, L.M., Lied, A.M., Edwards, L.S., Settle, A.H., Capurso, D., Llaca, V., Deschamps, S., Cigan, M., Young, J.K., May, A.P.: Mapping the genomic landscape of CRISPR-Cas9 cleavage. Nat. Methods 14(6), 600&ndash;606 (2017). <a href="https://www.ncbi.nlm.nih.gov/pubmed/28459459">PMID 28459459</a></li> </ol> <p>## Contact</p> <p>ferro@rth.dk gorodkin@rth.dk</p>